• Bulletin of the Korean Mathematical Society
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• v.49 no.4
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• pp.851-861
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• 2012

In this paper, we define the notion of statistical A-summability for double sequences and find its relation with A-statistical convergence. We apply our new method of summability to prove a Korovkin-type approximation theorem for a function of two variables. Furthermore, through an example, it is shown that our theorem is stronger than classical and statistical cases.

• Korean Journal of Mathematics
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• v.30 no.1
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• pp.155-160
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• 2022

Let X be a partial metric space generated by a partial metric p. In this paper, we introduce the notions of statistical convergence and strongly Cesàro summability in partial metric spaces. Also, we investigate the relations between the statistical convergence and strongly Cesàro summability.

• Journal of applied mathematics & informatics
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• v.40 no.1_2
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• pp.327-339
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• 2022

In this paper, we introduce arithmetic ${\mathcal{I}}$-statistically convergent sequence space $A{\mathcal{I}}SC$, ${\mathcal{I}}$-lacunary arithmetic statistically convergent sequence space $A{\mathcal{I}}SC_{\theta}$, strongly ${\mathcal{I}}$-lacunary arithmetic convergent sequence space $AN_{\theta}[{\mathcal{I}}]$ and prove some inclusion relations between these spaces. Futhermore, we give ${\mathcal{I}}$-lacunary arithmetic statistical continuity. Finally, we define ${\mathcal{I}}$-Cesàro arithmetic summability, strongly ${\mathcal{I}}$-Cesàro arithmetic summability. Also, we investigate the relationship between the concepts of strongly ${\mathcal{I}}$-Cesàro arithmetic summability, strongly ${\mathcal{I}}$-lacunary arithmetic summability and arithmetic ${\mathcal{I}}$ -statistically convergence.

• Kyungpook Mathematical Journal
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• v.56 no.2
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• pp.357-366
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• 2016

In this paper, deferred statistical convergence is defined by using deferred $Ces{\grave{a}}ro$ mean instead of $Ces{\grave{a}}ro$ mean in the definition of statistical convergence. The obtained method is compared with strong deferred $Ces{\grave{a}}ro$ mean and statistical convergence under some certain assumptions. Also, some inclusion theorems and examples are given.

• Journal of applied mathematics & informatics
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• v.37 no.5_6
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• pp.459-467
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• 2019

In this work, via Orlicz functions, we have obtained a generalization of rough statistical convergence of asymptotically equivalent triple sequences a new non-matrix convergence method, which is intermediate between the ordinary convergence and the rough statistical convergence. We also have examined some inclusion relations related to this concept. We obtain the results are non negative real numbers with respect to the partial order on the set of real numbers.

• Journal of applied mathematics & informatics
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• v.42 no.2
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• pp.245-256
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• 2024

This article introduces the notion of almost deferred weighted convergence, statistical deferred weighted almost convergence and almost deferred weighted statistical convergence for real valued sequences. Further, with the aid of interesting examples, we investigated some relationships among our proposed methods. Moreover, we prove a new type of approximation theorem and demonstrated that our theorem effectively extends and improves most of the earlier existing results. Finally, we have presented an example which proves that our theorem is a stronger than its classical versions.

• Kyungpook Mathematical Journal
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• v.58 no.1
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• pp.91-103
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• 2018

In this paper, we generalize the concept of deferred density to that of deferred f-density, where f is an unbounded modulus and introduce a new non-matrix convergence method, namely deferred f-statistical convergence or $S^f_{p,q}$-convergence. Apart from studying the $K{\ddot{o}}the$-Toeplitz duals of $S^f_{p,q}$, the space of deferred f-statistically convergent sequences, a decomposition theorem is also established. We also introduce a notion of strongly deferred $Ces{\grave{a}}ro$ summable sequences defined by modulus f and investigate the relationship between deferred f-statistical convergence and strongly deferred $Ces{\grave{a}}ro$ summable sequences defined by f.